Facial key points are feature points of facial features. A facial key point positioning is to positioning the feature points of the facial features, which is a very important technique in a facial image analysis. A quality of a positioning result of the feature points of the facial features directly affects multiple back-end technologies such as a face beautification and a face recognition. Therefore, it is very important to give an accurate evaluation on the quality of the positioning result of the feature points of the facial features.
In the conventional art, the evaluation on the facial key point positioning result needs to be dependent on human. There are two solutions as follows.
In solution 1, coordinates of points are marked manually in advance. Coordinates of key points of the facial features are marked manually on a facial image, and are stored as a real value. In a case that a positioning algorithm for the key points of the facial features gives result coordinates of the key points, the average distance between the result coordinates and the manually marked coordinates is used for evaluating the quality of the positioning result.
In solution 2, a manual subjective evaluation is performed. The quality of the facial key point positioning result is determined by performing the manual subjective evaluation. By using multiple facial key point positioning algorithm or using randomness of the positioning algorithm, multiple positioning results of facial features are outputted for the same facial image, and then a most accurate result is selected from the multiple positioning results by performing the manual subjective evaluation.
In solution 1, key points of the facial features are marked manually on the facial image. Generally, it takes several minutes to mark coordinates, which is of high labor costs and long time-consuming. This evaluation method is used in a comparison of multiple positioning algorithms for the key points of the facial features.
In solution 2, a manual subjective comparison is performed. By manually comparing the positioning results of the coordinates of the key points, quality of two positioning results is determined based on a subjective judgment. This subjective evaluation has a few requirements for the face, and takes only a few seconds to be completed in a case that the number of results is not many. Although this evaluation method has already been used in some products, but it has obvious disadvantages. Firstly, this evaluation method has stronge subjective and cannot be quantified. Secondly, in a case that the number of results to be compared is large, comparison difficulty is increased and time consumed for manual evaluation increases significantly. Accordingly, the reliability of the evaluation is reduced.
The above two solutions require manual intervention, which is time-consuming and of low efficiency. Furthermore, the positioning results cannot be quantified.